{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T07:56:46.839246Z",
     "start_time": "2020-11-03T07:56:46.785974Z"
    }
   },
   "outputs": [],
   "source": [
    "import tensorflow.compat.v1 as tf\n",
    "from tensorflow import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T07:56:29.369868Z",
     "start_time": "2020-11-03T07:56:29.354320Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.2.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T07:57:03.483405Z",
     "start_time": "2020-11-03T07:57:03.473593Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /root/anaconda3/envs/mytf/lib/python3.8/site-packages/tensorflow/python/compat/v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "non-resource variables are not supported in the long term\n"
     ]
    }
   ],
   "source": [
    "tf.disable_v2_behavior()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T07:57:30.182286Z",
     "start_time": "2020-11-03T07:57:30.176835Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.2.0'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T07:59:43.517277Z",
     "start_time": "2020-11-03T07:59:29.120937Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
      "32768/29515 [=================================] - 0s 11us/step\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
      "26427392/26421880 [==============================] - 6s 0us/step\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
      "8192/5148 [===============================================] - 0s 0us/step\n",
      "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
      "4423680/4422102 [==============================] - 3s 1us/step\n"
     ]
    }
   ],
   "source": [
    "fashion_mnist=keras.datasets.fashion_mnist\n",
    "(train_images,train_labels),(test_images,test_labels)=fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T08:01:12.874598Z",
     "start_time": "2020-11-03T08:01:12.868049Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T08:05:25.704348Z",
     "start_time": "2020-11-03T08:05:25.494086Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.imshow(train_images[710])\n",
    "plt.colorbar()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-11-03T08:05:31.289832Z",
     "start_time": "2020-11-03T08:05:31.283499Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_labels[710]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
